Multiclass support vector machine-based lesion mapping predicts functional outcome in ischemic stroke patients

PLoS ONE

Volumn 10, Issue 6, 2015, Pages

  Forkert, Nils Daniel ^a   Verleger, Tobias ^b   Cheng, Bastian ^b   Thomalla, Götz ^b   Hilgetag, Claus C ^b,c   Fiehler, Jens ^b  

^a UNIVERSITY OF CALGARY   (Canada)

^b UNIVERSITY MEDICAL CENTER HAMBURG EPPENDORF   (Germany)

^c BOSTON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; BRAIN INFARCTION SIZE; BRAIN ISCHEMIA; BRAIN MAPPING; BRAIN REGION; COMPUTER PREDICTION; DATA BASE; FEMALE; FUNCTIONAL STATUS; HUMAN; MAJOR CLINICAL STUDY; MALE; MEASUREMENT ACCURACY; MIDDLE CEREBRAL ARTERY; NATIONAL INSTITUTES OF HEALTH STROKE SCALE; NUCLEAR MAGNETIC RESONANCE IMAGING; RANKIN SCALE; SUPPORT VECTOR MACHINE; BIOLOGICAL MODEL; MIDDLE AGED; PATHOPHYSIOLOGY; STROKE;

AGED; BRAIN ISCHEMIA; BRAIN MAPPING; FEMALE; HUMANS; MALE; MIDDLE AGED; MODELS, NEUROLOGICAL; STROKE; SUPPORT VECTOR MACHINE;

EID: 84938915091     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0129569     Document Type: Article

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